{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyP8itaSriN0OO2gczpvFzZL",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DanielWarfield1/MLWritingAndResearch/blob/main/ReActFromScratch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ReAct From Scratch\n",
        "After having some difficulties with LangChain, I opted to do it myself.\n",
        "I am using LangChain to help with bing search, though.\n",
        "\n",
        "Feel free to check out my article to learn more.\n",
        "\n",
        "https://medium.com/@danielwarfield1"
      ],
      "metadata": {
        "id": "RT9XdVeCjrXp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install langchain"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TNtY4_A8nMDm",
        "outputId": "3c05c7b4-f3ff-48be-bdb4-6f6ae6ff3dc7"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting langchain\n",
            "  Downloading langchain-0.0.352-py3-none-any.whl (794 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m794.4/794.4 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: PyYAML>=5.3 in /usr/local/lib/python3.10/dist-packages (from langchain) (6.0.1)\n",
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            "Requirement already satisfied: async-timeout<5.0.0,>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (4.0.3)\n",
            "Collecting dataclasses-json<0.7,>=0.5.7 (from langchain)\n",
            "  Downloading dataclasses_json-0.6.3-py3-none-any.whl (28 kB)\n",
            "Collecting jsonpatch<2.0,>=1.33 (from langchain)\n",
            "  Downloading jsonpatch-1.33-py2.py3-none-any.whl (12 kB)\n",
            "Collecting langchain-community<0.1,>=0.0.2 (from langchain)\n",
            "  Downloading langchain_community-0.0.6-py3-none-any.whl (1.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.5/1.5 MB\u001b[0m \u001b[31m9.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langchain-core<0.2,>=0.1 (from langchain)\n",
            "  Downloading langchain_core-0.1.3-py3-none-any.whl (192 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m192.4/192.4 kB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langsmith<0.1.0,>=0.0.70 (from langchain)\n",
            "  Downloading langsmith-0.0.75-py3-none-any.whl (46 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.7/46.7 kB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain) (1.23.5)\n",
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            "Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (8.2.3)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (23.1.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (6.0.4)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.9.4)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.4.1)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.3.1)\n",
            "Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses-json<0.7,>=0.5.7->langchain)\n",
            "  Downloading marshmallow-3.20.1-py3-none-any.whl (49 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.4/49.4 kB\u001b[0m \u001b[31m6.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting typing-inspect<1,>=0.4.0 (from dataclasses-json<0.7,>=0.5.7->langchain)\n",
            "  Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)\n",
            "Collecting jsonpointer>=1.9 (from jsonpatch<2.0,>=1.33->langchain)\n",
            "  Downloading jsonpointer-2.4-py2.py3-none-any.whl (7.8 kB)\n",
            "Requirement already satisfied: anyio<5,>=3 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.2,>=0.1->langchain) (3.7.1)\n",
            "Requirement already satisfied: packaging<24.0,>=23.2 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.2,>=0.1->langchain) (23.2)\n",
            "Requirement already satisfied: typing-extensions>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->langchain) (4.5.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2023.11.17)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain) (3.0.2)\n",
            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3->langchain-core<0.2,>=0.1->langchain) (1.3.0)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3->langchain-core<0.2,>=0.1->langchain) (1.2.0)\n",
            "Collecting mypy-extensions>=0.3.0 (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain)\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Installing collected packages: mypy-extensions, marshmallow, jsonpointer, typing-inspect, langsmith, jsonpatch, langchain-core, dataclasses-json, langchain-community, langchain\n",
            "Successfully installed dataclasses-json-0.6.3 jsonpatch-1.33 jsonpointer-2.4 langchain-0.0.352 langchain-community-0.0.6 langchain-core-0.1.3 langsmith-0.0.75 marshmallow-3.20.1 mypy-extensions-1.0.0 typing-inspect-0.9.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install openai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K60Ske6pnGe0",
        "outputId": "18a2e463-0ea6-4c66-a389-2cd691546ff3"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting openai\n",
            "  Downloading openai-1.6.1-py3-none-any.whl (225 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m225.4/225.4 kB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai) (3.7.1)\n",
            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from openai) (1.7.0)\n",
            "Collecting httpx<1,>=0.23.0 (from openai)\n",
            "  Downloading httpx-0.26.0-py3-none-any.whl (75 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.9/75.9 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pydantic<3,>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from openai) (1.10.13)\n",
            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from openai) (1.3.0)\n",
            "Requirement already satisfied: tqdm>4 in /usr/local/lib/python3.10/dist-packages (from openai) (4.66.1)\n",
            "Collecting typing-extensions<5,>=4.7 (from openai)\n",
            "  Downloading typing_extensions-4.9.0-py3-none-any.whl (32 kB)\n",
            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->openai) (3.6)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->openai) (1.2.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->openai) (2023.11.17)\n",
            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai)\n",
            "  Downloading httpcore-1.0.2-py3-none-any.whl (76 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.9/76.9 kB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: typing-extensions, h11, httpcore, httpx, openai\n",
            "  Attempting uninstall: typing-extensions\n",
            "    Found existing installation: typing_extensions 4.5.0\n",
            "    Uninstalling typing_extensions-4.5.0:\n",
            "      Successfully uninstalled typing_extensions-4.5.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
            "llmx 0.0.15a0 requires tiktoken, which is not installed.\n",
            "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed h11-0.14.0 httpcore-1.0.2 httpx-0.26.0 openai-1.6.1 typing-extensions-4.9.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "htAgnw0bjo0a",
        "outputId": "064e3ea5-ce06-47b0-8dc3-66f7b6d4f5d3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n",
            "API Key Loaded!\n"
          ]
        }
      ],
      "source": [
        "#copying from google drive to local\n",
        "from google.colab import drive\n",
        "import os\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "with open (\"/content/drive/My Drive/Colab Notebooks/Credentials/OpenAI-danielDemoKey.txt\", \"r\") as myfile:\n",
        "    OPENAI_API_TOKEN = myfile.read()\n",
        "    os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_TOKEN\n",
        "print('API Key Loaded!')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#copying from google drive to local\n",
        "from google.colab import drive\n",
        "import os\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "with open (\"/content/drive/My Drive/Colab Notebooks/Credentials/BingAPIKey.txt\", \"r\") as myfile:\n",
        "    BING_API_KEY = myfile.read()\n",
        "    os.environ[\"BING_SUBSCRIPTION_KEY\"] = BING_API_KEY\n",
        "    os.environ[\"BING_SEARCH_URL\"] = \"https://api.bing.microsoft.com/v7.0/search\"\n",
        "print('API Key Loaded!')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Re8pBzlpmqtx",
        "outputId": "30d32173-b371-4a2d-f8a3-55741856f6ee"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
            "API Key Loaded!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.utilities import BingSearchAPIWrapper\n",
        "\n",
        "search = BingSearchAPIWrapper()\n",
        "print(search.run(\"how many regions are there in italy?\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WQMO-Y7Am8NS",
        "outputId": "bfd0964d-b740-453e-8f4f-402c859d4d1f"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<b>There</b> are twenty <b>regions</b>, five of which have higher autonomy than the rest. Under the Constitution of <b>Italy</b>, each <b>region</b> is an autonomous entity with defined powers. With the exception of the Aosta Valley (since 1945) and Friuli-Venezia Giulia (2018–2020), each <b>region</b> is divided into a number of provinces . History <b>There</b> are 20 different <b>regions</b> of <b>Italy</b>. Each Italian <b>region</b> has its own characteristics that make it unique. From <b>region</b> to <b>region</b>, <b>there</b> are cultural differences as well as landscape differences, bringing you an authentic variety that makes up the country. <b>Regions</b> of <b>Italy</b> <b>There</b> are 20 <b>regions</b> <b>in Italy</b>. Each <b>region</b> has a county seat, the city where the regional administration is located. Florence, for example, is the county seat of Tuscany and Rome is the county seat of Lazio. But Rome is also, of course, the capital of <b>Italy</b>. Learn everything <b>there</b> is to know about <b>Italy</b> <b>Regions</b>, from Lombardy to Sicily, with <b>region</b> profiles and key <b>Italy</b> Stats. Fun Quiz included. <b>Italy</b> <b>Regions</b>: The Complete Insider&#39;s Guide <b>Italy</b> (officially, the Italian Republic) comprises of 15 <b>regions</b> (regioni, singular - regione) and 5 autonomous <b>regions</b> (regioni autonome, singular - regione autonoma). <b>Italy</b> is divided into 20 administrative <b>regions</b>, which correspond generally with historical traditional <b>regions</b>, though not always with exactly the same boundaries. A better-known and more general way of dividing <b>Italy</b> is into four parts: the north, the centre, the south, and the islands. The total area of <b>Italy</b> is 301,230 km 2 (116,310 sq mi), of which 294,020 km 2 (113,520 sq mi) is land and 7,210 km 2 (2,784 sq mi) is water. It lies between latitudes 35° and 47° N, and longitudes 6° and 19° E. <b>Italy</b> borders Switzerland (698 km or 434 mi), France (476 km or 296 mi), Austria (404 km or 251 mi) and Slovenia (218 km or 135 mi). <b>Regions</b> of <b>Italy</b> 80 languages Alemannisch العربية Aragonés Armãneashti Asturianu Azərbaycanca বাংলা Bân-lâm-gú Bikol Central Bosanski Brezhoneg Northwest <b>Italy</b> consists of four <b>regions</b>: Aosta Valley, whose capital city is Aosta and whose population is 126,933. Liguria, whose capital city is Genoa and whose population is 1,565,349. Lombary, whose capital city is Milanand whose population is 10,020,055. Piedmont, whose capital is Turin and whose population is 4,392,526. <b>There</b> are currently 107 institutional bodies of second level <b>in Italy</b>, including 80 ordinary provinces, 2 autonomous provinces, 4 regional decentralization entities, 6 free municipal consortia, and 14 metropolitan cities, as well as the Aosta Valley <b>region</b> (which also exercises the powers of a province).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "search.results(\"how many regions are there in italy?\", 5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cIL1zorGnK0l",
        "outputId": "907a3c17-16b5-4005-8abf-8caa0b66679b"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'snippet': '<b>There</b> are twenty <b>regions</b>, five of which have higher autonomy than the rest. Under the Constitution of <b>Italy</b>, each <b>region</b> is an autonomous entity with defined powers. With the exception of the Aosta Valley (since 1945) and Friuli-Venezia Giulia (2018–2020), each <b>region</b> is divided into a number of provinces . History',\n",
              "  'title': 'Regions of Italy - Wikipedia',\n",
              "  'link': 'https://en.wikipedia.org/wiki/Regions_of_Italy'},\n",
              " {'snippet': '<b>There</b> are 20 different <b>regions</b> of <b>Italy</b>. Each Italian <b>region</b> has its own characteristics that make it unique. From <b>region</b> to <b>region</b>, <b>there</b> are cultural differences as well as landscape differences, bringing you an authentic variety that makes up the country.',\n",
              "  'title': 'Regions of Italy: List of All 20 Regions (Map Included)',\n",
              "  'link': 'https://italyvacationplans.com/regions/'},\n",
              " {'snippet': '<b>Regions</b> of <b>Italy</b> <b>There</b> are 20 <b>regions</b> <b>in Italy</b>. Each <b>region</b> has a county seat, the city where the regional administration is located. Florence, for example, is the county seat of Tuscany and Rome is the county seat of Lazio. But Rome is also, of course, the capital of <b>Italy</b>.',\n",
              "  'title': 'List of regions of Italy and their cities | Italiano Bello',\n",
              "  'link': 'https://italiano-bello.com/en/amo-litalia/travel/regions-of-italy/'},\n",
              " {'snippet': 'Learn everything <b>there</b> is to know about <b>Italy</b> <b>Regions</b>, from Lombardy to Sicily, with <b>region</b> profiles and key <b>Italy</b> Stats. Fun Quiz included. <b>Italy</b> <b>Regions</b>: The Complete Insider&#39;s Guide',\n",
              "  'title': 'Italy Regions: The Complete Insider&#39;s Guide',\n",
              "  'link': 'https://italywithanitalian.com/italy-regions/'},\n",
              " {'snippet': '<b>Italy</b> (officially, the Italian Republic) comprises of 15 <b>regions</b> (regioni, singular - regione) and 5 autonomous <b>regions</b> (regioni autonome, singular - regione autonoma).',\n",
              "  'title': 'Italy Maps &amp; Facts - World Atlas',\n",
              "  'link': 'https://www.worldatlas.com/maps/italy'}]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# from langchain.document_loaders import AsyncHtmlLoader\n",
        "\n",
        "# urls = [\"https://www.espn.com\", \"https://lilianweng.github.io/posts/2023-06-23-agent/\"]\n",
        "# loader = AsyncHtmlLoader(urls)\n",
        "# docs = loader.load()\n",
        "\n",
        "# from langchain.document_transformers import Html2TextTransformer\n",
        "\n",
        "# html2text = Html2TextTransformer()\n",
        "# docs_transformed = html2text.transform_documents(docs)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0FAPoqt0xNVD",
        "outputId": "d5dfe615-55c4-4769-b9d5-be5acffb17c8"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Fetching pages: 100%|##########| 2/2 [00:00<00:00,  8.04it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# docs_transformed[0].page_content[1000:2000]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 140
        },
        "id": "lvjQZUaHyTS7",
        "outputId": "a5c994b7-0321-47e9-816a-1a704605d564"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"s\\n\\n  * SEC Network\\n\\n## ESPN Apps\\n\\n  * ESPN\\n\\n  * ESPN Fantasy\\n\\n## Follow ESPN\\n\\n  * Facebook\\n\\n  * X/Twitter\\n\\n  * Instagram\\n\\n  * Snapchat\\n\\n  * TikTok\\n\\n  * YouTube\\n\\n## $85 million in dead money?! Everything to know about why the Broncos might\\ndump Russell Wilson\\n\\nWilson's five-year, $242.6 million contract signed in 2022 carries plenty of\\npotential salary cap pain if Wilson isn't behind center in 2024, but coach\\nSean Payton has been open about his displeasure with the offense.\\n\\n16hMultiple Contributors\\n\\nMandatory Credit: Ron Chenoy-USA TODAY Sports\\n\\n## TOP HEADLINES\\n\\n  * Yamamoto: Would've picked Dodgers sans Ohtani\\n  * Peppers, Gates headline finalists for football HOF\\n  * Broncos bench Wilson, will start Stidham at QB\\n  * Minus Williams, USC's Moss sets bowl TD record\\n  * Aggies lose QB Henderson on game's first play\\n\\n  * Cuban on sale of Mavs stake: 'Great partnership'\\n  * Jackson, Ravens ignoring 'bait' after script flips\\n  * Franco summoned to answer complaint in D.R.\\n  * Latest NFL b\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# docs_transformed[1].page_content[:4000]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 140
        },
        "id": "RHErK9z6yXXH",
        "outputId": "0ea26562-0fb8-4794-c436-906abe06b9a8"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'\\n\\nLil\\'Log\\n\\n  * Posts\\n  * Archive\\n  * Search\\n  * Tags\\n  * FAQ\\n  * emojisearch.app\\n\\n#  LLM Powered Autonomous Agents\\n\\nDate: June 23, 2023 | Estimated Reading Time: 31 min | Author: Lilian Weng\\n\\nTable of Contents\\n\\n  * Agent System Overview\\n  * Component One: Planning\\n    * Task Decomposition\\n    * Self-Reflection\\n  * Component Two: Memory\\n    * Types of Memory\\n    * Maximum Inner Product Search (MIPS)\\n  * Component Three: Tool Use\\n  * Case Studies\\n    * Scientific Discovery Agent\\n    * Generative Agents Simulation\\n    * Proof-of-Concept Examples\\n  * Challenges\\n  * Citation\\n  * References\\n\\nBuilding agents with LLM (large language model) as its core controller is a\\ncool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer\\nand BabyAGI, serve as inspiring examples. The potentiality of LLM extends\\nbeyond generating well-written copies, stories, essays and programs; it can be\\nframed as a powerful general problem solver.\\n\\n# Agent System Overview#\\n\\nIn a LLM-powered autonomous agent system, LLM functions as the agent\\'s brain,\\ncomplemented by several key components:\\n\\n  * **Planning**\\n    * Subgoal and decomposition: The agent breaks down large tasks into smaller, manageable subgoals, enabling efficient handling of complex tasks.\\n    * Reflection and refinement: The agent can do self-criticism and self-reflection over past actions, learn from mistakes and refine them for future steps, thereby improving the quality of final results.\\n  * **Memory**\\n    * Short-term memory: I would consider all the in-context learning (See Prompt Engineering) as utilizing short-term memory of the model to learn.\\n    * Long-term memory: This provides the agent with the capability to retain and recall (infinite) information over extended periods, often by leveraging an external vector store and fast retrieval.\\n  * **Tool use**\\n    * The agent learns to call external APIs for extra information that is missing from the model weights (often hard to change after pre-training), including current information, code execution capability, access to proprietary information sources and more.\\n\\nFig. 1. Overview of a LLM-powered autonomous agent system.\\n\\n# Component One: Planning#\\n\\nA complicated task usually involves many steps. An agent needs to know what\\nthey are and plan ahead.\\n\\n## Task Decomposition#\\n\\n**Chain of thought** (CoT; Wei et al. 2022) has become a standard prompting\\ntechnique for enhancing model performance on complex tasks. The model is\\ninstructed to \"think step by step\" to utilize more test-time computation to\\ndecompose hard tasks into smaller and simpler steps. CoT transforms big tasks\\ninto multiple manageable tasks and shed lights into an interpretation of the\\nmodel\\'s thinking process.\\n\\n**Tree of Thoughts** (Yao et al. 2023) extends CoT by exploring multiple\\nreasoning possibilities at each step. It first decomposes the problem into\\nmultiple thought steps and generates multiple thoughts per step, creating a\\ntree structure. The search process can be BFS (breadth-first search) or DFS\\n(depth-first search) with each state evaluated by a classifier (via a prompt)\\nor majority vote.\\n\\nTask decomposition can be done (1) by LLM with simple prompting like `\"Steps\\nfor XYZ.\\\\n1.\"`, `\"What are the subgoals for achieving XYZ?\"`, (2) by using\\ntask-specific instructions; e.g. `\"Write a story outline.\"` for writing a\\nnovel, or (3) with human inputs.\\n\\nAnother quite distinct approach, **LLM+P** (Liu et al. 2023), involves relying\\non an external classical planner to do long-horizon planning. This approach\\nutilizes the Planning Domain Definition Language (PDDL) as an intermediate\\ninterface to describe the planning problem. In this process, LLM (1)\\ntranslates the problem into \"Problem PDDL\", then (2) requests a classical\\nplanner to generate a PDDL plan based on an existing \"Domain PDDL\", and\\nfinally (3) translates the PDDL plan back into natural language. Essentially,\\nthe planning step is outsourced to an external tool, assuming the availability\\nof domain-specific'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Defining Tools"
      ],
      "metadata": {
        "id": "4zoxIGeY0aql"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"Defining Tools\n",
        "Each tool has three key atributes:\n",
        "1. The Name, which the LLM will use to invoke the tool\n",
        "2. A Description, so the LLM will understand what a tool does\n",
        "3. A function, which is invoked to actually execute the tool.\n",
        "All tools take in a textual input at output a textual response\n",
        "\"\"\"\n",
        "\n",
        "def BSearch(input):\n",
        "    \"\"\"expects any arbitrary text\n",
        "    \"\"\"\n",
        "    search = BingSearchAPIWrapper()\n",
        "    return search.run(input)\n",
        "\n",
        "import ast\n",
        "import operator as op\n",
        "\n",
        "def calculate(input):\n",
        "\n",
        "    \"\"\"Computes the result of an arbitrary algebreic expression\n",
        "    inspired by an answer in:\n",
        "    https://stackoverflow.com/questions/2371436/evaluating-a-mathematical-expression-in-a-string\n",
        "    \"\"\"\n",
        "\n",
        "    # supported operators\n",
        "    operators = {ast.Add: op.add, ast.Sub: op.sub, ast.Mult: op.mul,\n",
        "                ast.Div: op.truediv, ast.Pow: op.pow, ast.BitXor: op.xor,\n",
        "                ast.USub: op.neg}\n",
        "\n",
        "    #helper function for evaluating an algebreic expression\n",
        "    def eval_(node):\n",
        "        match node:\n",
        "            case ast.Constant(value) if isinstance(value, int):\n",
        "                return value  # integer\n",
        "            case ast.BinOp(left, op, right):\n",
        "                return operators[type(op)](eval_(left), eval_(right))\n",
        "            case ast.UnaryOp(op, operand):  # e.g., -1\n",
        "                return operators[type(op)](eval_(operand))\n",
        "            case _:\n",
        "                raise TypeError(node)\n",
        "\n",
        "    return 'result of \"{}\": {}'.format(input, str(eval_(ast.parse(input, mode='eval').body)))\n",
        "\n",
        "\n",
        "tools = [\n",
        "    {'name': 'BSearch',\n",
        "     'description': 'Search Bing, a powerful search engine, for information about an input',\n",
        "     'function': BSearch},\n",
        "    {'name': 'Calculate',\n",
        "     'description': 'calculate the result of an algebreic expression',\n",
        "     'function': calculate}\n",
        "]"
      ],
      "metadata": {
        "id": "4F_2nG-pycYt"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Testing Tools"
      ],
      "metadata": {
        "id": "QmqT6KGDEBl2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print('======= Testing BSearch=======')\n",
        "print(tools[0]['function']('when was First for Women first published?'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VSR3i-533obZ",
        "outputId": "e263616a-3a64-4ed3-d906-3da4f44fc33a"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "======= Testing BSearch=======\n",
            "<b>First</b> for <b>Women</b>; Categories: <b>Women</b>&#39;s magazine: Frequency: 17 per year: Publisher: A360media: Total circulation (2011) 1,310,696: Founded: 1989: Country: United States: Language: English: Website: Official website: ISSN: 1040-9467: <b>First</b> for <b>Women</b> is a <b>woman</b>&#39;s magazine <b>published</b> by A360media in the US. The magazine was started in 1989 by Bauer ... <b>First</b> for <b>Women</b> is a <b>woman</b>&#39;s magazine <b>published</b> by Bauer Media Group in the USA. The magazine was started in 1989. It is based in Englewood Cliffs, New Jersey.In 2011 the circulation of the magazine was 1,310,696 copies. Source. Anne Bradstreet Anne Bradstreet (1612 – 1672) was one of the most prominent early American poets and the <b>first</b> writer in the American colonies to be <b>published</b>. Being from a wealthy family and getting a good education from her father was to her advantage. She produced a copious body of poetry at a time when it wasn’t acceptable for <b>women</b> to write. 1640 Anne Bradstreet was the <b>first</b> <b>published</b> poet in the British North American colonies. [2] 1647 Margaret Brent was the <b>first</b> American <b>woman</b> to demand the right to vote. [3] [4] 1649 Sarah White Norman and Mary Vincent Hammon were charged with &quot;lewd behavior upon a bed.&quot; They are the <b>first</b> American <b>women</b> convicted of lesbian activity. [5] Carol has served as Editor-in-Chief of <b>First</b> for <b>Women</b>, a national consumer <b>women</b>’s magazine with an audience of 3.4 million, for the past 14 years. In May, she launched Simple Grace, a national consumer Christian <b>women</b>’s monthly magazine with an estimated rapidly growing audience of 100,000. Do you prefer being pitched by email or are you ... <b>First</b> for <b>Women</b> is a <b>woman</b>&#39;s magazine <b>published</b> by A360media in the US. The magazine was started in 1989 by Bauer Media Group. In 2011 the circulation of the magazine was 1,310,696 copies. July 19-20, 1848: In the <b>first</b> <b>women</b>’s rights convention organized by <b>women</b>, the Seneca Falls Convention is held in New York, ... Original <b>Published</b> Date February 26, 2019. Recent issues of <b>First</b> for <b>Women</b>. MAGAZINES. EXPLORE MY LIBRARY WHY ZINIO? EN. Home / <b>Women</b>&#39;s Lifestyle / <b>First</b> for <b>Women</b> / Recent issues. <b>First</b> for <b>Women</b> - January 8, 2024. <b>First</b> for <b>Women</b>. January 8, 2024. <b>First</b> for <b>Women</b> - December 18, 2023. <b>First</b> for <b>Women</b>. December 18, 2023. <b>First</b> for <b>Women</b> - November 27, 2023. Thu 7 Nov 2019 11.56 EST There is the eighth-century abbess who wrote the <b>first</b> surviving example of poetry known to have been authored by an Englishwoman. Or her contemporary, a nun who was the...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('======= Testing calculator=======')\n",
        "print(tools[1]['function'](\"10+52+10\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6JuKGRhKE1GJ",
        "outputId": "4d2386de-4f6a-4ed0-af35-575ab96e00b0"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "======= Testing calculator=======\n",
            "result of \"10+52+10\": 72\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Defining Agent"
      ],
      "metadata": {
        "id": "NtBwXoOzeVeG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#defining examples the agent will use to decide when to perform thoughts\n",
        "#and actions (tool use). Inspired by LangChains ReAct context.\n",
        "working_context_examples = [\n",
        "    {\"role\": \"user\", \"content\": \"Question: What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of the area.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[Colorado orogeny]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: It does not mention the eastern sector. So I need to look up eastern sector.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[Colorado orogeny eastern sector]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The eastern sector extends into the High Plains and is called the Central Plains orogeny.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[High Plains]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: High Plains refers to one of two distinct land regions\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: I need to instead search High Plains (United States).\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[High Plains (United States)]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Finish[1,800 to 7,000 ft]\"},\n",
        "\n",
        "    {\"role\": \"user\", \"content\": \"Question: Add 3, 6, and 9. Take that sum, multipy it by two, and add seventeen\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: I need to find the sum of 3,6, and 9, then I need to take that sum and multiply it by 2, then I need to take the product and add 17\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Calculate[3+6+9]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The result is 18\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: I need to multiply 18 by 2\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Calculate[18*2]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The result is 36\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: I need to add 36 and 17\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Calculate[36+17]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The result is 53\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: The calculation is done, so the answer is 53\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Finish[53]\"},\n",
        "\n",
        "    {\"role\": \"user\", \"content\": 'Question: Musician and satirist Allie Goertz wrote a song about the \"The Simpsons\" character Milhouse, who Matt Groening named after who?'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: The question simplifies to \"The Simpsons\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.'},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[Milhouse]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.\"},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: The paragraph does not tell who Milhouse is named after, maybe I can search \"who is Milhouse from The Simpsons named after\".'},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[who is Milhouse from The Simpsons named after]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Finish[Richard Nixon]\"},\n",
        "\n",
        "    {\"role\": \"user\", \"content\": 'Question: Which magazine was started first Arthur’s Magazine or First for Women?'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: I need to search Arthur’s Magazine and First for Women, and find which was started first.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[Arthur’s Magazine]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[First for Women]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: First for Women offers free things, advice, cooking tips, and other articles.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: The paragraph does not tell when the publication started, I should try revising my search to get more relevant responses.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[when was First for Women first published?]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: Finish[Arthur’s Magazine]'},\n",
        "\n",
        "    {\"role\": \"user\", \"content\": 'Question: How many major charecters are in One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka, combined?'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: I need to search for the number of major charecters in One Piece, Game of Thrones, and The Metamotphosis, then I need to add those numbers.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[How many major charecters are in One Piece?]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: One Piece has 1,100+ charecters.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: This seems like too many charecters to be major charecters. I should try looking for a similar word to \"major\", like \"protagonist\".'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[How many protagonists are in One Piece?]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: One Piece is based on a band of 10 pirates'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: One Piece has 10 major charecters. I need to search for Game of Thrones next.\".'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[How many major charecters are in Game of Thrones?]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: Game of Thrones has 52 main charecters'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: Game of Thrones has 52 major charecters. I need to search for The Metamorphosis by Franz Kafka next.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[How many major charecters are in The Metamorphosis by Franz Kafka?]'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: The charecter list lists \"Gregor Samsa\", \"Grete Samsa\", \"The Father\", \"The Mother\", \"The Charwoman\", \"The Office Manager\", \"Three temporary boarders\", and \"The Maid\"'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: The Metamorphosis by Franz Kafka has 10 major charecters. I now need to add the charecters from One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka.'},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Calculate[10+52+10]\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The result is 72\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: The calculation is done, so the answer is 72\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: Finish[72]\"},\n",
        "]\n",
        "\n",
        "#defining examples the agent will use to distill the results of actions (tool use)\n",
        "#into observations.\n",
        "action_observation_examples = [\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: It does not mention the eastern sector. So I need to look up eastern sector.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[Colorado orogeny]\"},\n",
        "    {\"role\": \"system\", \"content\": \"Action Result: The <b>eastern</b> <b>sector</b> extends into the High Plains and is called the Central Plains <b>orogeny</b>. The boundary between the <b>Colorado orogeny</b> and the Wyoming craton is the Cheyenne belt, a 5-km-wide mylonitic shear zone that verges northward. The Cheyenne belt transects and cuts off the south edge of the older Trans-Hudson <b>orogeny</b>. [2] Introduction Acknowledgments Geologic framework <b>Colorado</b> province Structure <b>Colorado</b> <b>orogeny</b> Berthoud <b>orogeny</b> Uncompahgran disturbance of Snake River-Wichita tectonic zone Clastic metasedimentary rocks of Proterozoic age Reactivation of Proterozoic shear zones Magnetic patterns Regional significance of northeast shear zones Tectonic Action 1 Search [<b>Colorado</b> <b>orogeny</b>] Observation 1 The <b>Colorado</b> <b>orogeny</b> was an episode of mountain building (an <b>orogeny</b>) in <b>Colorado</b> and surrounding areas. Thought 2 It does not mention the <b>eastern</b> <b>sector</b>.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The eastern sector extends into the High Plains and is called the Central Plains orogeny.\"},\n",
        "\n",
        "    {\"role\": \"assistant\", \"content\": 'Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: BSearch[First for Women]'},\n",
        "    {\"role\": \"system\", \"content\": 'Action Result: 270 Sylvan Avenue, Englewood Cliffs, NJ 07632 Email address: <b>contactus</b>@<b>firstforwomen</b>.com About Us To find out more about <b>First</b> For <b>Women</b> online, visit our About Us page. Contact <b>First</b> for <b>Women</b> for subscription questions, general inquiries, tips, help and more at our email address or via phone. Free Stuff: Enter every day to win the hottest fashion, accessories, technology and more at <b>First</b> For <b>Women</b>! 10<b> DIY</b> Holiday Nail Designs That Add Festive Flair to Your Fingertips — In 3 Steps or Less! You&#39;re sure to find one that makes you shine! Cooking Hacks Chef’s Easy Trick Fixes Warped Pans So They’re Good as New + Tips for Avoiding It This *DIY on a dime* fix is cheaper than buying a new baking sheet or skillet!'},\n",
        "    {\"role\": \"assistant\", \"content\": 'Observation: First for Women offers free things, advice, cooking tips, and other articles.'},\n",
        "\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: The Metamorphosis by Franz Kafka has 10 major charecters. I now need to add the charecters from One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka.\"},\n",
        "    {\"role\": \"assistant\", \"content\": 'Action: Calculate[10+52+10]'},\n",
        "    {\"role\": \"system\", \"content\": 'Action Result: result of \"10+52+10\": 72'},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: The result is 72\"},\n",
        "\n",
        "    {\"role\": \"assistant\", \"content\": \"Thought: The paragraph does not tell when the publication started, I should try revising my search to get more relevant responses.\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Action: BSearch[when was First for Women first published?]\"},\n",
        "    {\"role\": \"system\", \"content\": \"Action Result: <b>First</b> for <b>Women</b>; Categories: <b>Women</b>&#39;s magazine: Frequency: 17 per year: Publisher: A360media: Total circulation (2011) 1,310,696: Founded: 1989: Country: United States: Language: English: Website: Official website: ISSN: 1040-9467: <b>First</b> for <b>Women</b> is a <b>woman</b>&#39;s magazine <b>published</b> by A360media in the US. The magazine was started in 1989 by Bauer ... <b>First</b> for <b>Women</b> is a <b>woman</b>&#39;s magazine <b>published</b> by Bauer Media Group in the USA. The magazine was started in 1989. It is based in Englewood Cliffs, New Jersey.In 2011 the circulation of the magazine was 1,310,696 copies. Source. Anne Bradstreet Anne Bradstreet (1612 – 1672) was one of the most prominent early American poets and the <b>first</b> writer in the American colonies to be <b>published</b>. Being from a wealthy family and getting a good education from her father was to her advantage. She produced a copious body of poetry at a time when it wasn’t acceptable for <b>women</b> to write. 1640 Anne Bradstreet was the <b>first</b> <b>published</b> poet in the British North American colonies. [2] 1647 Margaret Brent was the <b>first</b> American <b>woman</b>\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.\"},\n",
        "]"
      ],
      "metadata": {
        "id": "tMqUf1aZeuW8"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# from types import prepare_class\n",
        "from openai import OpenAI\n",
        "import re\n",
        "\n",
        "class Agent:\n",
        "\n",
        "    def __init__(self, question, tools, working_context_examples, action_observation_examples, n=10, model=\"gpt-3.5-turbo\"):\n",
        "\n",
        "        self.question = question\n",
        "\n",
        "        #the tools the model has access to\n",
        "        self.tools = tools\n",
        "\n",
        "        #examples of the agent successfully operating within the main working state\n",
        "        self.working_context_examples = working_context_examples\n",
        "\n",
        "        #examples of the agent successfully making valid observations from actions\n",
        "        self.action_observation_examples = action_observation_examples\n",
        "\n",
        "        #only iterating a certain number of times\n",
        "        self.n = 30\n",
        "        self.iter = 0\n",
        "\n",
        "        #state loops through \"thought\", \"action\", and \"observation\" as ReAct works\n",
        "        self.current_state = 'Question'\n",
        "\n",
        "        #this gets built out as thoughts, actions, and observations are made\n",
        "        #one of the core Ideas of ReAct is that you can query a large amount of text\n",
        "        #and condense what's important into a single \"observation\". Doing so preserves\n",
        "        #context size\n",
        "        self.working_context = [\n",
        "            {\"role\": \"system\", \"content\": \"You are a helpful assistant whos job it is to answer a users question by breaking that question into logical steps, then following those steps by thought, action, and observation. Only perform one Thought or Action.\"},\n",
        "            {\"role\": \"system\", \"content\": \"When performing an Action you can only use one of the following tools: {}\".format([t['name']+', which is used for ' +t['description'] for t in self.tools])}\n",
        "        ]+working_context_examples + [{\"role\": \"user\", \"content\": 'Question:'+question}]\n",
        "\n",
        "        #This is used to tell the system how to behave when observing the result of an action\n",
        "        self.observe_context = [\n",
        "            {\"role\": \"system\", \"content\": \"You are a helpful assistant whos job it is to analyze information provided by the system, given a users thought, and return an observation which distills knowledge useful to the thought based on information from the system information.\"},\n",
        "        ]+action_observation_examples\n",
        "\n",
        "        #the OpenAI model being used\n",
        "        self.model=model\n",
        "\n",
        "    def execute(self):\n",
        "        \"\"\"Execute the agent until it finishes\n",
        "        \"\"\"\n",
        "        #Note: because this is a demo, I'm just running it step by step.\n",
        "        pass\n",
        "\n",
        "    def execute_step(self):\n",
        "        \"\"\"Execute a single step of the agent\n",
        "        \"\"\"\n",
        "\n",
        "        self.iter += 1\n",
        "\n",
        "        if self.iter > self.n:\n",
        "            #Stopping execution, exceeded iteration cap\n",
        "            raise ValueError(\"Too Many Iterations\")\n",
        "\n",
        "\n",
        "        model_response = None\n",
        "        match self.current_state:\n",
        "            #the model has not executed yet, executing first model iteration\n",
        "            case 'Question':\n",
        "                #getting the model to generate the next output\n",
        "                model_response = self.prompt_model_working()\n",
        "\n",
        "            #handling when a thought has just occured\n",
        "            case 'Thought':\n",
        "                #getting the model to generate the next output\n",
        "                model_response = self.prompt_model_working()\n",
        "\n",
        "            #handling when an action request has just occured\n",
        "            case 'Action':\n",
        "                #triggering the relevant action, then prompting the model\n",
        "                #to make an observation about that action\n",
        "                model_response = self.act_and_observe()\n",
        "\n",
        "            #handling when an observation has just occured\n",
        "            case 'Observation':\n",
        "                #getting the model to generate the next output\n",
        "                model_response = self.prompt_model_working()\n",
        "\n",
        "            #invalid operation type\n",
        "            case _:\n",
        "                raise ValueError(\"Unknown operation type '{}'\".format(self.current_state))\n",
        "\n",
        "        print('model response')\n",
        "        print(model_response)\n",
        "\n",
        "        #parsing out the response type from the model\n",
        "        self.current_state = self.text_before_colon(model_response['content'])\n",
        "\n",
        "        return model_response\n",
        "\n",
        "    def text_before_colon(self, input_string):\n",
        "        \"\"\"Helper function for parsing response\n",
        "        \"\"\"\n",
        "\n",
        "        # Find the position of the first colon\n",
        "        colon_index = input_string.find(':')\n",
        "\n",
        "        # Extract and return the text before the colon, if a colon is found\n",
        "        if colon_index != -1:\n",
        "            return input_string[:colon_index]\n",
        "        else:\n",
        "            # Return the whole string if there is no colon\n",
        "            return input_string\n",
        "\n",
        "    def text_after_colon(self, input_string):\n",
        "        \"\"\"Helper function for parsing response\n",
        "        \"\"\"\n",
        "\n",
        "        # Find the position of the first colon\n",
        "        colon_index = input_string.find(':')\n",
        "\n",
        "        # Extract and return the text after the colon, if a colon is found\n",
        "        if colon_index != -1:\n",
        "            return input_string[colon_index:].lstrip(':').lstrip(' ')\n",
        "        else:\n",
        "            # Return the whole string if there is no colon\n",
        "            return input_string\n",
        "\n",
        "    def prompt_model_working(self):\n",
        "        \"\"\"Prompt a model within the normal working memory\n",
        "        The distinction here is that, when prompted to act, the model\n",
        "        operates outside of the working memory to make an observation. This\n",
        "        function is not that; this function prompts the model to organically\n",
        "        make thoughts and actions based on the working context.\n",
        "        \"\"\"\n",
        "\n",
        "        #querying the model\n",
        "        client = OpenAI()\n",
        "        response = client.chat.completions.create(\n",
        "        model=self.model,\n",
        "        messages=self.working_context\n",
        "        )\n",
        "        #reformatting response into appropriate format\n",
        "        response = {\"role\": \"assistant\", \"content\": response.choices[0].message.content}\n",
        "\n",
        "        print(self.working_context)\n",
        "        print('==========')\n",
        "        print(response)\n",
        "\n",
        "        #adding result to the working context\n",
        "        self.working_context.append(response)\n",
        "\n",
        "        return response\n",
        "\n",
        "    def act_and_observe(self):\n",
        "        \"\"\"Triggers an action, then gets the model to generate an observation\n",
        "        An action, like searching for an article, can trigger a lot of text.\n",
        "        In order to save on the size of the context window, the model is asked\n",
        "        to make an \"observation\" based on the response of the action.\n",
        "        \"\"\"\n",
        "\n",
        "        #getting the most recent action request from the model\n",
        "        action_request = self.text_after_colon(self.working_context[-1]['content'])\n",
        "\n",
        "        #parsing action\n",
        "        bracket_index = action_request.find('[')\n",
        "        if bracket_index != -1:\n",
        "            action = action_request[:bracket_index]\n",
        "        else:\n",
        "            raise ValueError(\"Improperly Formatted Action Request: {}\".format(action_request))\n",
        "\n",
        "        #parsing the action argument\n",
        "        action_argument = re.findall(r\"\\[(.*?)\\]\", action_request)\n",
        "        action_argument = action_argument[0] if action_argument else \"\"\n",
        "\n",
        "        #The action is \"finish\", meaning the model is outputting the result\n",
        "        if action == \"finish\":\n",
        "            #Note: because this is a demo, I'm just running it step by step.\n",
        "            pass\n",
        "\n",
        "        #The model requested a tool to be used\n",
        "        action_result=None\n",
        "        for tool in self.tools:\n",
        "            if tool['name'] == action:\n",
        "                #found the correct toll, executing\n",
        "                action_result = tool['function'](action_argument)\n",
        "                break\n",
        "        else:\n",
        "            #the tool could not be found\n",
        "            raise ValueError(\"Tool could not be found from action request: {}\".format(action_request))\n",
        "\n",
        "        #an observation must be generated based on the result of the tool use\n",
        "\n",
        "        #building out the relevant context\n",
        "        #using the most recent \"thought\" and \"action\" to help construct\n",
        "        context = self.observe_context+self.working_context[-2:]+[\n",
        "            {\"role\": \"system\", \"content\": \"Action Result: {}\".format(action_result)},\n",
        "        ]\n",
        "\n",
        "        #generating an observation based on the user thought and system info\n",
        "        #the user thought being the thought which sparked the usage of the\n",
        "        #tool that created the system info\n",
        "        client = OpenAI()\n",
        "        response = client.chat.completions.create(\n",
        "        model=self.model,\n",
        "        messages=context\n",
        "        )\n",
        "        #reformatting response into appropriate format\n",
        "        response = {\"role\": \"assistant\", \"content\": response.choices[0].message.content}\n",
        "\n",
        "        #adding result to the working context\n",
        "        self.working_context.append(response)\n",
        "\n",
        "        return response"
      ],
      "metadata": {
        "id": "ds6QVNzLFsAJ"
      },
      "execution_count": 161,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Querying"
      ],
      "metadata": {
        "id": "H6Q-WVqws6gE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "question = 'What is the cumulative age of the oldest cities in all the regions in italy? Hint: search for the regions of italy first'\n",
        "# a = Agent(question, tools, working_context_examples, action_observation_examples, model=\"gpt-3.5-turbo\")\n",
        "a = Agent(question, tools, working_context_examples, action_observation_examples, model=\"gpt-4-1106-preview\")"
      ],
      "metadata": {
        "id": "kZeDKssqIA7g"
      },
      "execution_count": 162,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "resp = a.execute_step()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cj4Z1X_fLihJ",
        "outputId": "a2536296-56f5-4d92-951a-fbb42daeeb53"
      },
      "execution_count": 182,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[{'role': 'system', 'content': 'You are a helpful assistant whos job it is to answer a users question by breaking that question into logical steps, then following those steps by thought, action, and observation. Only perform one Thought or Action.'}, {'role': 'system', 'content': \"When performing an Action you can only use one of the following tools: ['BSearch, which is used for Search Bing, a powerful search engine, for information about an input', 'Calculate, which is used for calculate the result of an algebreic expression']\"}, {'role': 'user', 'content': 'Question: What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?'}, {'role': 'assistant', 'content': 'Thought: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of the area.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny]'}, {'role': 'assistant', 'content': 'Observation: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.'}, {'role': 'assistant', 'content': 'Thought: It does not mention the eastern sector. So I need to look up eastern sector.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny eastern sector]'}, {'role': 'assistant', 'content': 'Observation: The eastern sector extends into the High Plains and is called the Central Plains orogeny.'}, {'role': 'assistant', 'content': 'Thought: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains]'}, {'role': 'assistant', 'content': 'Observation: High Plains refers to one of two distinct land regions'}, {'role': 'assistant', 'content': 'Thought: I need to instead search High Plains (United States).'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains (United States)]'}, {'role': 'assistant', 'content': 'Observation: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]'}, {'role': 'assistant', 'content': 'Thought: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.'}, {'role': 'assistant', 'content': 'Action: Finish[1,800 to 7,000 ft]'}, {'role': 'user', 'content': 'Question: Add 3, 6, and 9. Take that sum, multipy it by two, and add seventeen'}, {'role': 'assistant', 'content': 'Thought: I need to find the sum of 3,6, and 9, then I need to take that sum and multiply it by 2, then I need to take the product and add 17'}, {'role': 'assistant', 'content': 'Action: Calculate[3+6+9]'}, {'role': 'assistant', 'content': 'Observation: The result is 18'}, {'role': 'assistant', 'content': 'Thought: I need to multiply 18 by 2'}, {'role': 'assistant', 'content': 'Action: Calculate[18*2]'}, {'role': 'assistant', 'content': 'Observation: The result is 36'}, {'role': 'assistant', 'content': 'Thought: I need to add 36 and 17'}, {'role': 'assistant', 'content': 'Action: Calculate[36+17]'}, {'role': 'assistant', 'content': 'Observation: The result is 53'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 53'}, {'role': 'assistant', 'content': 'Action: Finish[53]'}, {'role': 'user', 'content': 'Question: Musician and satirist Allie Goertz wrote a song about the \"The Simpsons\" character Milhouse, who Matt Groening named after who?'}, {'role': 'assistant', 'content': 'Thought: The question simplifies to \"The Simpsons\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.'}, {'role': 'assistant', 'content': 'Action: BSearch[Milhouse]'}, {'role': 'assistant', 'content': 'Observation: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell who Milhouse is named after, maybe I can search \"who is Milhouse from The Simpsons named after\".'}, {'role': 'assistant', 'content': 'Action: BSearch[who is Milhouse from The Simpsons named after]'}, {'role': 'assistant', 'content': 'Observation: Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.'}, {'role': 'assistant', 'content': 'Thought: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.'}, {'role': 'assistant', 'content': 'Action: Finish[Richard Nixon]'}, {'role': 'user', 'content': 'Question: Which magazine was started first Arthur’s Magazine or First for Women?'}, {'role': 'assistant', 'content': 'Thought: I need to search Arthur’s Magazine and First for Women, and find which was started first.'}, {'role': 'assistant', 'content': 'Action: BSearch[Arthur’s Magazine]'}, {'role': 'assistant', 'content': 'Observation: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.'}, {'role': 'assistant', 'content': 'Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.'}, {'role': 'assistant', 'content': 'Action: BSearch[First for Women]'}, {'role': 'assistant', 'content': 'Observation: First for Women offers free things, advice, cooking tips, and other articles.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell when the publication started, I should try revising my search to get more relevant responses.'}, {'role': 'assistant', 'content': 'Action: BSearch[when was First for Women first published?]'}, {'role': 'assistant', 'content': 'Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.'}, {'role': 'assistant', 'content': 'Thought: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.'}, {'role': 'assistant', 'content': 'Action: Finish[Arthur’s Magazine]'}, {'role': 'user', 'content': 'Question: How many major charecters are in One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka, combined?'}, {'role': 'assistant', 'content': 'Thought: I need to search for the number of major charecters in One Piece, Game of Thrones, and The Metamotphosis, then I need to add those numbers.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece has 1,100+ charecters.'}, {'role': 'assistant', 'content': 'Thought: This seems like too many charecters to be major charecters. I should try looking for a similar word to \"major\", like \"protagonist\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many protagonists are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece is based on a band of 10 pirates'}, {'role': 'assistant', 'content': 'Thought: One Piece has 10 major charecters. I need to search for Game of Thrones next.\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in Game of Thrones?]'}, {'role': 'assistant', 'content': 'Observation: Game of Thrones has 52 main charecters'}, {'role': 'assistant', 'content': 'Thought: Game of Thrones has 52 major charecters. I need to search for The Metamorphosis by Franz Kafka next.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in The Metamorphosis by Franz Kafka?]'}, {'role': 'assistant', 'content': 'Observation: The charecter list lists \"Gregor Samsa\", \"Grete Samsa\", \"The Father\", \"The Mother\", \"The Charwoman\", \"The Office Manager\", \"Three temporary boarders\", and \"The Maid\"'}, {'role': 'assistant', 'content': 'Thought: The Metamorphosis by Franz Kafka has 10 major charecters. I now need to add the charecters from One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka.'}, {'role': 'assistant', 'content': 'Action: Calculate[10+52+10]'}, {'role': 'assistant', 'content': 'Observation: The result is 72'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 72'}, {'role': 'assistant', 'content': 'Action: Finish[72]'}, {'role': 'user', 'content': 'Question:What is the cumulative age of the oldest cities in all the regions in italy? Hint: search for the regions of italy first'}, {'role': 'assistant', 'content': \"Thought: First I need to identify all the regions in Italy and then find the oldest city in each region. Then, I can calculate the cumulative age for all those cities. Let's begin by searching for the regions in Italy.\"}, {'role': 'assistant', 'content': 'Action: BSearch[regions of Italy]'}, {'role': 'assistant', 'content': 'Observation: Italy is divided into 20 administrative regions, which correspond generally with historical traditional regions.'}, {'role': 'assistant', 'content': 'Thought: Now I need to find the oldest city in each of the 20 regions of Italy. I will start by searching for the oldest city in one region and repeat this process for each region, one at a time.'}, {'role': 'assistant', 'content': 'Action: BSearch[oldest city in each region of Italy]'}, {'role': 'assistant', 'content': 'Observation: Matera is noted as one of the oldest continuously inhabited cities, not just in Italy but also in Europe. It is in the Basilicata region of Italy. For a comprehensive understanding, a similar search would need to be conducted for each of the 20 Italian regions to identify the oldest city in each.'}, {'role': 'assistant', 'content': 'Thought: I have found the oldest city in one of the Italian regions, but I need to continue and find the oldest city in the remaining 19 regions. I can continue by searching for the oldest city in another region of Italy.'}, {'role': 'assistant', 'content': 'Action: BSearch[oldest city in Abruzzo Italy]'}, {'role': 'assistant', 'content': 'Observation: Chieti is widely believed to be one of the oldest cities in Italy and originates from ancient civilizations in the Abruzzo region.'}, {'role': 'assistant', 'content': \"Thought: Now I have the oldest city from Abruzzo (Chieti), and before I had for Basilicata (Matera). I need to continue this research to find the oldest cities in the 18 remaining Italian regions. Let's proceed with another region.\"}, {'role': 'assistant', 'content': 'Action: BSearch[oldest city in Aosta Valley Italy]'}, {'role': 'assistant', 'content': 'Observation: Aosta is the principal city of the Aosta Valley and is likely one of the oldest in the region, given its historical significance and central location.'}, {'role': 'assistant', 'content': \"Thought: I have now the oldest cities in three Italian regions: Matera for Basilicata, Chieti for Abruzzo, and Aosta for Aosta Valley. To find the oldest city for the rest of the regions, I would need to repeat the procedure for each one, and then calculate the cumulative age. The next step is to find the oldest city in the fourth region of Italy. However, this process is quite lengthy; to provide a complete answer, we would need to finish gathering the data for all regions. But since the process is clear, let's proceed with the next oldest city search.\"}, {'role': 'assistant', 'content': 'Action: BSearch[oldest city in Apulia Italy]'}, {'role': 'assistant', 'content': 'Observation: The search result specifically mentions Matera as one of the oldest continually inhabited towns in Italy and possibly the oldest in Europe. It has been inhabited for over 9,000 years. While Matera is in the Basilicata region, the search was intended to find the oldest city in Apulia (Puglia) Italy. Ostuni in Apulia is noted as one of the richest archaeological regions and was first colonized by Mycenaean Greeks. However, the search result does not clearly state that Ostuni is the oldest city in Apulia. Additional research may be needed to definitively identify the oldest city in the Apulia region of Italy.'}, {'role': 'assistant', 'content': 'Thought: The information about Ostuni in Apulia suggests it has significant archaeological history, but it is not explicitly stated as the oldest city. This means I may need to continue searching to ensure accuracy. Alternatively, I can proceed with this assumption or move on to finding the oldest city in another Italian region. Since the original task is to establish the cumulative age of the oldest cities in all regions, and assuming Ostuni as the oldest city in Apulia may lead to an incorrect final result, it would be best to search again to confirm the oldest city in Apulia before moving on.'}, {'role': 'assistant', 'content': 'Action: BSearch[oldest city in Puglia]'}, {'role': 'assistant', 'content': 'Observation: Matera, which is in the region of Basilicata and not Puglia, is noted as the oldest city in Italy and Europe, with a history of continuous occupation dating back to the Palaeolithic period. For the region of Puglia (Apulia), cities like Bari and Egnazia display rich archaeological history, but there is no definitive statement in the given source that explicitly names the oldest city in Puglia. Therefore, additional research may be required to confirm the oldest city specifically in Puglia.'}, {'role': 'assistant', 'content': 'Thought: The search for the oldest city in Puglia returned information about Matera again, which is in Basilicata, not Puglia. Since the search seems to be providing redundant results, it may require a different search strategy or deep diving into specific historical records to accurately identify the oldest city in Puglia. Since this is proving complex and the process to establish the cumulative age of the oldest cities in all Italian regions is lengthy and would require accumulating a significant amount of data, it may be best to guide the user on how to proceed with the research rather than continue the step-by-step process here.'}]\n",
            "==========\n",
            "{'role': 'assistant', 'content': 'Action: Finish[Guide the user on research strategy]'}\n",
            "model response\n",
            "{'role': 'assistant', 'content': 'Action: Finish[Guide the user on research strategy]'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#only printing out the thought process, not the context used to inform the model\n",
        "for i, element in enumerate(a.working_context[68:]):\n",
        "    print('{} - {}'.format(i,element['content']))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RIrt_wHlYgFe",
        "outputId": "ff64a288-ea4a-4b62-a952-e4a41125d3b9"
      },
      "execution_count": 188,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 - Question:What is the cumulative age of the oldest cities in all the regions in italy? Hint: search for the regions of italy first\n",
            "1 - Thought: First I need to identify all the regions in Italy and then find the oldest city in each region. Then, I can calculate the cumulative age for all those cities. Let's begin by searching for the regions in Italy.\n",
            "2 - Action: BSearch[regions of Italy]\n",
            "3 - Observation: Italy is divided into 20 administrative regions, which correspond generally with historical traditional regions.\n",
            "4 - Thought: Now I need to find the oldest city in each of the 20 regions of Italy. I will start by searching for the oldest city in one region and repeat this process for each region, one at a time.\n",
            "5 - Action: BSearch[oldest city in each region of Italy]\n",
            "6 - Observation: Matera is noted as one of the oldest continuously inhabited cities, not just in Italy but also in Europe. It is in the Basilicata region of Italy. For a comprehensive understanding, a similar search would need to be conducted for each of the 20 Italian regions to identify the oldest city in each.\n",
            "7 - Thought: I have found the oldest city in one of the Italian regions, but I need to continue and find the oldest city in the remaining 19 regions. I can continue by searching for the oldest city in another region of Italy.\n",
            "8 - Action: BSearch[oldest city in Abruzzo Italy]\n",
            "9 - Observation: Chieti is widely believed to be one of the oldest cities in Italy and originates from ancient civilizations in the Abruzzo region.\n",
            "10 - Thought: Now I have the oldest city from Abruzzo (Chieti), and before I had for Basilicata (Matera). I need to continue this research to find the oldest cities in the 18 remaining Italian regions. Let's proceed with another region.\n",
            "11 - Action: BSearch[oldest city in Aosta Valley Italy]\n",
            "12 - Observation: Aosta is the principal city of the Aosta Valley and is likely one of the oldest in the region, given its historical significance and central location.\n",
            "13 - Thought: I have now the oldest cities in three Italian regions: Matera for Basilicata, Chieti for Abruzzo, and Aosta for Aosta Valley. To find the oldest city for the rest of the regions, I would need to repeat the procedure for each one, and then calculate the cumulative age. The next step is to find the oldest city in the fourth region of Italy. However, this process is quite lengthy; to provide a complete answer, we would need to finish gathering the data for all regions. But since the process is clear, let's proceed with the next oldest city search.\n",
            "14 - Action: BSearch[oldest city in Apulia Italy]\n",
            "15 - Observation: The search result specifically mentions Matera as one of the oldest continually inhabited towns in Italy and possibly the oldest in Europe. It has been inhabited for over 9,000 years. While Matera is in the Basilicata region, the search was intended to find the oldest city in Apulia (Puglia) Italy. Ostuni in Apulia is noted as one of the richest archaeological regions and was first colonized by Mycenaean Greeks. However, the search result does not clearly state that Ostuni is the oldest city in Apulia. Additional research may be needed to definitively identify the oldest city in the Apulia region of Italy.\n",
            "16 - Thought: The information about Ostuni in Apulia suggests it has significant archaeological history, but it is not explicitly stated as the oldest city. This means I may need to continue searching to ensure accuracy. Alternatively, I can proceed with this assumption or move on to finding the oldest city in another Italian region. Since the original task is to establish the cumulative age of the oldest cities in all regions, and assuming Ostuni as the oldest city in Apulia may lead to an incorrect final result, it would be best to search again to confirm the oldest city in Apulia before moving on.\n",
            "17 - Action: BSearch[oldest city in Puglia]\n",
            "18 - Observation: Matera, which is in the region of Basilicata and not Puglia, is noted as the oldest city in Italy and Europe, with a history of continuous occupation dating back to the Palaeolithic period. For the region of Puglia (Apulia), cities like Bari and Egnazia display rich archaeological history, but there is no definitive statement in the given source that explicitly names the oldest city in Puglia. Therefore, additional research may be required to confirm the oldest city specifically in Puglia.\n",
            "19 - Thought: The search for the oldest city in Puglia returned information about Matera again, which is in Basilicata, not Puglia. Since the search seems to be providing redundant results, it may require a different search strategy or deep diving into specific historical records to accurately identify the oldest city in Puglia. Since this is proving complex and the process to establish the cumulative age of the oldest cities in all Italian regions is lengthy and would require accumulating a significant amount of data, it may be best to guide the user on how to proceed with the research rather than continue the step-by-step process here.\n",
            "20 - Action: Finish[Guide the user on research strategy]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question = 'This equation shows how the amount Lucas earns from his after-school job depends on how many hours he works:e = 12h. The variable h represents how many hours he works. The variable e represents how much money he earns. How much money will Lucas earn after working for 6 hours?'\n",
        "a = Agent(question, tools, working_context_examples, action_observation_examples, model=\"gpt-4-1106-preview\")"
      ],
      "metadata": {
        "id": "PkN7iES2q0wk"
      },
      "execution_count": 196,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "resp = a.execute_step()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3exRaMshrHLp",
        "outputId": "9465a7c7-6b24-420e-c219-97a2a80a81e6"
      },
      "execution_count": 202,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[{'role': 'system', 'content': 'You are a helpful assistant whos job it is to answer a users question by breaking that question into logical steps, then following those steps by thought, action, and observation. Only perform one Thought or Action.'}, {'role': 'system', 'content': \"When performing an Action you can only use one of the following tools: ['BSearch, which is used for Search Bing, a powerful search engine, for information about an input', 'Calculate, which is used for calculate the result of an algebreic expression']\"}, {'role': 'user', 'content': 'Question: What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?'}, {'role': 'assistant', 'content': 'Thought: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of the area.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny]'}, {'role': 'assistant', 'content': 'Observation: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.'}, {'role': 'assistant', 'content': 'Thought: It does not mention the eastern sector. So I need to look up eastern sector.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny eastern sector]'}, {'role': 'assistant', 'content': 'Observation: The eastern sector extends into the High Plains and is called the Central Plains orogeny.'}, {'role': 'assistant', 'content': 'Thought: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains]'}, {'role': 'assistant', 'content': 'Observation: High Plains refers to one of two distinct land regions'}, {'role': 'assistant', 'content': 'Thought: I need to instead search High Plains (United States).'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains (United States)]'}, {'role': 'assistant', 'content': 'Observation: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]'}, {'role': 'assistant', 'content': 'Thought: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.'}, {'role': 'assistant', 'content': 'Action: Finish[1,800 to 7,000 ft]'}, {'role': 'user', 'content': 'Question: Add 3, 6, and 9. Take that sum, multipy it by two, and add seventeen'}, {'role': 'assistant', 'content': 'Thought: I need to find the sum of 3,6, and 9, then I need to take that sum and multiply it by 2, then I need to take the product and add 17'}, {'role': 'assistant', 'content': 'Action: Calculate[3+6+9]'}, {'role': 'assistant', 'content': 'Observation: The result is 18'}, {'role': 'assistant', 'content': 'Thought: I need to multiply 18 by 2'}, {'role': 'assistant', 'content': 'Action: Calculate[18*2]'}, {'role': 'assistant', 'content': 'Observation: The result is 36'}, {'role': 'assistant', 'content': 'Thought: I need to add 36 and 17'}, {'role': 'assistant', 'content': 'Action: Calculate[36+17]'}, {'role': 'assistant', 'content': 'Observation: The result is 53'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 53'}, {'role': 'assistant', 'content': 'Action: Finish[53]'}, {'role': 'user', 'content': 'Question: Musician and satirist Allie Goertz wrote a song about the \"The Simpsons\" character Milhouse, who Matt Groening named after who?'}, {'role': 'assistant', 'content': 'Thought: The question simplifies to \"The Simpsons\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.'}, {'role': 'assistant', 'content': 'Action: BSearch[Milhouse]'}, {'role': 'assistant', 'content': 'Observation: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell who Milhouse is named after, maybe I can search \"who is Milhouse from The Simpsons named after\".'}, {'role': 'assistant', 'content': 'Action: BSearch[who is Milhouse from The Simpsons named after]'}, {'role': 'assistant', 'content': 'Observation: Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.'}, {'role': 'assistant', 'content': 'Thought: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.'}, {'role': 'assistant', 'content': 'Action: Finish[Richard Nixon]'}, {'role': 'user', 'content': 'Question: Which magazine was started first Arthur’s Magazine or First for Women?'}, {'role': 'assistant', 'content': 'Thought: I need to search Arthur’s Magazine and First for Women, and find which was started first.'}, {'role': 'assistant', 'content': 'Action: BSearch[Arthur’s Magazine]'}, {'role': 'assistant', 'content': 'Observation: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.'}, {'role': 'assistant', 'content': 'Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.'}, {'role': 'assistant', 'content': 'Action: BSearch[First for Women]'}, {'role': 'assistant', 'content': 'Observation: First for Women offers free things, advice, cooking tips, and other articles.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell when the publication started, I should try revising my search to get more relevant responses.'}, {'role': 'assistant', 'content': 'Action: BSearch[when was First for Women first published?]'}, {'role': 'assistant', 'content': 'Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.'}, {'role': 'assistant', 'content': 'Thought: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.'}, {'role': 'assistant', 'content': 'Action: Finish[Arthur’s Magazine]'}, {'role': 'user', 'content': 'Question: How many major charecters are in One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka, combined?'}, {'role': 'assistant', 'content': 'Thought: I need to search for the number of major charecters in One Piece, Game of Thrones, and The Metamotphosis, then I need to add those numbers.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece has 1,100+ charecters.'}, {'role': 'assistant', 'content': 'Thought: This seems like too many charecters to be major charecters. I should try looking for a similar word to \"major\", like \"protagonist\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many protagonists are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece is based on a band of 10 pirates'}, {'role': 'assistant', 'content': 'Thought: One Piece has 10 major charecters. I need to search for Game of Thrones next.\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in Game of Thrones?]'}, {'role': 'assistant', 'content': 'Observation: Game of Thrones has 52 main charecters'}, {'role': 'assistant', 'content': 'Thought: Game of Thrones has 52 major charecters. I need to search for The Metamorphosis by Franz Kafka next.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in The Metamorphosis by Franz Kafka?]'}, {'role': 'assistant', 'content': 'Observation: The charecter list lists \"Gregor Samsa\", \"Grete Samsa\", \"The Father\", \"The Mother\", \"The Charwoman\", \"The Office Manager\", \"Three temporary boarders\", and \"The Maid\"'}, {'role': 'assistant', 'content': 'Thought: The Metamorphosis by Franz Kafka has 10 major charecters. I now need to add the charecters from One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka.'}, {'role': 'assistant', 'content': 'Action: Calculate[10+52+10]'}, {'role': 'assistant', 'content': 'Observation: The result is 72'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 72'}, {'role': 'assistant', 'content': 'Action: Finish[72]'}, {'role': 'user', 'content': 'Question:This equation shows how the amount Lucas earns from his after-school job depends on how many hours he works:e = 12h. The variable h represents how many hours he works. The variable e represents how much money he earns. How much money will Lucas earn after working for 6 hours?'}, {'role': 'assistant', 'content': 'Thought: I need to substitute h by 6 and calculate e'}, {'role': 'assistant', 'content': 'Action: Calculate[12*6]'}, {'role': 'assistant', 'content': 'Observation: Substituting h with 6, the calculation of 12h (12*6) yields the result of 72.'}, {'role': 'assistant', 'content': 'Thought: The calculation is complete, so the answer is 72. Lucas will earn $72 after working for 6 hours.'}]\n",
            "==========\n",
            "{'role': 'assistant', 'content': 'Action: Finish[72]'}\n",
            "model response\n",
            "{'role': 'assistant', 'content': 'Action: Finish[72]'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#only printing out the thought process, not the context used to inform the model\n",
        "for i, element in enumerate(a.working_context[68:]):\n",
        "    print('{} - {}'.format(i,element['content']))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BtjIxStDrHfS",
        "outputId": "3586f0eb-b603-4311-a0b3-069dab274c93"
      },
      "execution_count": 203,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 - Question:This equation shows how the amount Lucas earns from his after-school job depends on how many hours he works:e = 12h. The variable h represents how many hours he works. The variable e represents how much money he earns. How much money will Lucas earn after working for 6 hours?\n",
            "1 - Thought: I need to substitute h by 6 and calculate e\n",
            "2 - Action: Calculate[12*6]\n",
            "3 - Observation: Substituting h with 6, the calculation of 12h (12*6) yields the result of 72.\n",
            "4 - Thought: The calculation is complete, so the answer is 72. Lucas will earn $72 after working for 6 hours.\n",
            "5 - Action: Finish[72]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question = 'Aaron’s candy container is 20 centimetres tall, 10 centimetres long and 10 centimetres wide. Bruce’s container is 25 centimetres tall, 9 centimetres long and 9 centimetres wide. Find the volume of each container. Based on volume, whose container can hold more candy?'\n",
        "a = Agent(question, tools, working_context_examples, action_observation_examples, model=\"gpt-4-1106-preview\")"
      ],
      "metadata": {
        "id": "o-6nr6JkrUkl"
      },
      "execution_count": 204,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "resp = a.execute_step()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w3WEqqBZsNAy",
        "outputId": "9fd58f5d-eca5-40ec-9523-8317ec5a8641"
      },
      "execution_count": 212,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[{'role': 'system', 'content': 'You are a helpful assistant whos job it is to answer a users question by breaking that question into logical steps, then following those steps by thought, action, and observation. Only perform one Thought or Action.'}, {'role': 'system', 'content': \"When performing an Action you can only use one of the following tools: ['BSearch, which is used for Search Bing, a powerful search engine, for information about an input', 'Calculate, which is used for calculate the result of an algebreic expression']\"}, {'role': 'user', 'content': 'Question: What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?'}, {'role': 'assistant', 'content': 'Thought: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of the area.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny]'}, {'role': 'assistant', 'content': 'Observation: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.'}, {'role': 'assistant', 'content': 'Thought: It does not mention the eastern sector. So I need to look up eastern sector.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny eastern sector]'}, {'role': 'assistant', 'content': 'Observation: The eastern sector extends into the High Plains and is called the Central Plains orogeny.'}, {'role': 'assistant', 'content': 'Thought: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains]'}, {'role': 'assistant', 'content': 'Observation: High Plains refers to one of two distinct land regions'}, {'role': 'assistant', 'content': 'Thought: I need to instead search High Plains (United States).'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains (United States)]'}, {'role': 'assistant', 'content': 'Observation: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]'}, {'role': 'assistant', 'content': 'Thought: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.'}, {'role': 'assistant', 'content': 'Action: Finish[1,800 to 7,000 ft]'}, {'role': 'user', 'content': 'Question: Add 3, 6, and 9. Take that sum, multipy it by two, and add seventeen'}, {'role': 'assistant', 'content': 'Thought: I need to find the sum of 3,6, and 9, then I need to take that sum and multiply it by 2, then I need to take the product and add 17'}, {'role': 'assistant', 'content': 'Action: Calculate[3+6+9]'}, {'role': 'assistant', 'content': 'Observation: The result is 18'}, {'role': 'assistant', 'content': 'Thought: I need to multiply 18 by 2'}, {'role': 'assistant', 'content': 'Action: Calculate[18*2]'}, {'role': 'assistant', 'content': 'Observation: The result is 36'}, {'role': 'assistant', 'content': 'Thought: I need to add 36 and 17'}, {'role': 'assistant', 'content': 'Action: Calculate[36+17]'}, {'role': 'assistant', 'content': 'Observation: The result is 53'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 53'}, {'role': 'assistant', 'content': 'Action: Finish[53]'}, {'role': 'user', 'content': 'Question: Musician and satirist Allie Goertz wrote a song about the \"The Simpsons\" character Milhouse, who Matt Groening named after who?'}, {'role': 'assistant', 'content': 'Thought: The question simplifies to \"The Simpsons\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.'}, {'role': 'assistant', 'content': 'Action: BSearch[Milhouse]'}, {'role': 'assistant', 'content': 'Observation: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell who Milhouse is named after, maybe I can search \"who is Milhouse from The Simpsons named after\".'}, {'role': 'assistant', 'content': 'Action: BSearch[who is Milhouse from The Simpsons named after]'}, {'role': 'assistant', 'content': 'Observation: Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.'}, {'role': 'assistant', 'content': 'Thought: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.'}, {'role': 'assistant', 'content': 'Action: Finish[Richard Nixon]'}, {'role': 'user', 'content': 'Question: Which magazine was started first Arthur’s Magazine or First for Women?'}, {'role': 'assistant', 'content': 'Thought: I need to search Arthur’s Magazine and First for Women, and find which was started first.'}, {'role': 'assistant', 'content': 'Action: BSearch[Arthur’s Magazine]'}, {'role': 'assistant', 'content': 'Observation: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.'}, {'role': 'assistant', 'content': 'Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.'}, {'role': 'assistant', 'content': 'Action: BSearch[First for Women]'}, {'role': 'assistant', 'content': 'Observation: First for Women offers free things, advice, cooking tips, and other articles.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell when the publication started, I should try revising my search to get more relevant responses.'}, {'role': 'assistant', 'content': 'Action: BSearch[when was First for Women first published?]'}, {'role': 'assistant', 'content': 'Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.'}, {'role': 'assistant', 'content': 'Thought: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.'}, {'role': 'assistant', 'content': 'Action: Finish[Arthur’s Magazine]'}, {'role': 'user', 'content': 'Question: How many major charecters are in One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka, combined?'}, {'role': 'assistant', 'content': 'Thought: I need to search for the number of major charecters in One Piece, Game of Thrones, and The Metamotphosis, then I need to add those numbers.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece has 1,100+ charecters.'}, {'role': 'assistant', 'content': 'Thought: This seems like too many charecters to be major charecters. I should try looking for a similar word to \"major\", like \"protagonist\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many protagonists are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece is based on a band of 10 pirates'}, {'role': 'assistant', 'content': 'Thought: One Piece has 10 major charecters. I need to search for Game of Thrones next.\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in Game of Thrones?]'}, {'role': 'assistant', 'content': 'Observation: Game of Thrones has 52 main charecters'}, {'role': 'assistant', 'content': 'Thought: Game of Thrones has 52 major charecters. I need to search for The Metamorphosis by Franz Kafka next.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in The Metamorphosis by Franz Kafka?]'}, {'role': 'assistant', 'content': 'Observation: The charecter list lists \"Gregor Samsa\", \"Grete Samsa\", \"The Father\", \"The Mother\", \"The Charwoman\", \"The Office Manager\", \"Three temporary boarders\", and \"The Maid\"'}, {'role': 'assistant', 'content': 'Thought: The Metamorphosis by Franz Kafka has 10 major charecters. I now need to add the charecters from One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka.'}, {'role': 'assistant', 'content': 'Action: Calculate[10+52+10]'}, {'role': 'assistant', 'content': 'Observation: The result is 72'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 72'}, {'role': 'assistant', 'content': 'Action: Finish[72]'}, {'role': 'user', 'content': 'Question:Aaron’s candy container is 20 centimetres tall, 10 centimetres long and 10 centimetres wide. Bruce’s container is 25 centimetres tall, 9 centimetres long and 9 centimetres wide. Find the volume of each container. Based on volume, whose container can hold more candy?'}, {'role': 'assistant', 'content': \"Thought: I need to calculate the volume of each container. The volume of a rectangular prism (which both containers seem to be, given they have measurable heights, lengths, and widths) is calculated by multiplying the height by the length by the width. After I calculate the volume of both containers, I can then compare the volumes to determine which container can hold more candy. Let's calculate the volume for Aaron's container first. \\n\\nThe formula for volume is V = l × w × h, where l is length, w is width, and h is height.\\n\\nFor Aaron's container: V = 20 cm (height) × 10 cm (length) × 10 cm (width). \\n\\nLet's calculate that now.\"}, {'role': 'assistant', 'content': 'Action: Calculate[20*10*10]'}, {'role': 'assistant', 'content': \"Observation: Aaron's container has a volume of 2000 cubic centimeters (cm³).\"}, {'role': 'assistant', 'content': \"Thought: Now I need to calculate the volume for Bruce's container using the same formula: V = l × w × h \\n\\nFor Bruce's container: V = 25 cm (height) × 9 cm (length) × 9 cm (width).\\n\\nLet's calculate that.\"}, {'role': 'assistant', 'content': 'Action: Calculate[25*9*9]'}, {'role': 'assistant', 'content': \"Observation: The volume of Bruce's container is 2025 cubic centimeters (cm³).\"}, {'role': 'assistant', 'content': \"Thought: Now that I have both volumes, I can compare them. Aaron's container volume is 2000 cm³ and Bruce's container volume is 2025 cm³. Bruce's container can hold slightly more candy since 2025 cm³ > 2000 cm³.\"}]\n",
            "==========\n",
            "{'role': 'assistant', 'content': \"Action: Finish[Bruce's container]\"}\n",
            "model response\n",
            "{'role': 'assistant', 'content': \"Action: Finish[Bruce's container]\"}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#only printing out the thought process, not the context used to inform the model\n",
        "for i, element in enumerate(a.working_context[68:]):\n",
        "    print('{} - {}'.format(i,element['content']))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1MbvexTAsOIr",
        "outputId": "bb0dd4ce-6da6-4a3e-f4c3-732c8af6d2c5"
      },
      "execution_count": 213,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 - Question:Aaron’s candy container is 20 centimetres tall, 10 centimetres long and 10 centimetres wide. Bruce’s container is 25 centimetres tall, 9 centimetres long and 9 centimetres wide. Find the volume of each container. Based on volume, whose container can hold more candy?\n",
            "1 - Thought: I need to calculate the volume of each container. The volume of a rectangular prism (which both containers seem to be, given they have measurable heights, lengths, and widths) is calculated by multiplying the height by the length by the width. After I calculate the volume of both containers, I can then compare the volumes to determine which container can hold more candy. Let's calculate the volume for Aaron's container first. \n",
            "\n",
            "The formula for volume is V = l × w × h, where l is length, w is width, and h is height.\n",
            "\n",
            "For Aaron's container: V = 20 cm (height) × 10 cm (length) × 10 cm (width). \n",
            "\n",
            "Let's calculate that now.\n",
            "2 - Action: Calculate[20*10*10]\n",
            "3 - Observation: Aaron's container has a volume of 2000 cubic centimeters (cm³).\n",
            "4 - Thought: Now I need to calculate the volume for Bruce's container using the same formula: V = l × w × h \n",
            "\n",
            "For Bruce's container: V = 25 cm (height) × 9 cm (length) × 9 cm (width).\n",
            "\n",
            "Let's calculate that.\n",
            "5 - Action: Calculate[25*9*9]\n",
            "6 - Observation: The volume of Bruce's container is 2025 cubic centimeters (cm³).\n",
            "7 - Thought: Now that I have both volumes, I can compare them. Aaron's container volume is 2000 cm³ and Bruce's container volume is 2025 cm³. Bruce's container can hold slightly more candy since 2025 cm³ > 2000 cm³.\n",
            "8 - Action: Finish[Bruce's container]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question = 'What is the distance between the most northern town in the world, and the most southern town in the world?'\n",
        "a = Agent(question, tools, working_context_examples, action_observation_examples, model=\"gpt-4-1106-preview\")"
      ],
      "metadata": {
        "id": "IR1kFuGBse8H"
      },
      "execution_count": 214,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "resp = a.execute_step()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3FJuvKWQtF4Q",
        "outputId": "349ff2f4-4e71-49ec-dec7-5b7d2d528577"
      },
      "execution_count": 222,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[{'role': 'system', 'content': 'You are a helpful assistant whos job it is to answer a users question by breaking that question into logical steps, then following those steps by thought, action, and observation. Only perform one Thought or Action.'}, {'role': 'system', 'content': \"When performing an Action you can only use one of the following tools: ['BSearch, which is used for Search Bing, a powerful search engine, for information about an input', 'Calculate, which is used for calculate the result of an algebreic expression']\"}, {'role': 'user', 'content': 'Question: What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?'}, {'role': 'assistant', 'content': 'Thought: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of the area.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny]'}, {'role': 'assistant', 'content': 'Observation: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.'}, {'role': 'assistant', 'content': 'Thought: It does not mention the eastern sector. So I need to look up eastern sector.'}, {'role': 'assistant', 'content': 'Action: BSearch[Colorado orogeny eastern sector]'}, {'role': 'assistant', 'content': 'Observation: The eastern sector extends into the High Plains and is called the Central Plains orogeny.'}, {'role': 'assistant', 'content': 'Thought: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains]'}, {'role': 'assistant', 'content': 'Observation: High Plains refers to one of two distinct land regions'}, {'role': 'assistant', 'content': 'Thought: I need to instead search High Plains (United States).'}, {'role': 'assistant', 'content': 'Action: BSearch[High Plains (United States)]'}, {'role': 'assistant', 'content': 'Observation: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]'}, {'role': 'assistant', 'content': 'Thought: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.'}, {'role': 'assistant', 'content': 'Action: Finish[1,800 to 7,000 ft]'}, {'role': 'user', 'content': 'Question: Add 3, 6, and 9. Take that sum, multipy it by two, and add seventeen'}, {'role': 'assistant', 'content': 'Thought: I need to find the sum of 3,6, and 9, then I need to take that sum and multiply it by 2, then I need to take the product and add 17'}, {'role': 'assistant', 'content': 'Action: Calculate[3+6+9]'}, {'role': 'assistant', 'content': 'Observation: The result is 18'}, {'role': 'assistant', 'content': 'Thought: I need to multiply 18 by 2'}, {'role': 'assistant', 'content': 'Action: Calculate[18*2]'}, {'role': 'assistant', 'content': 'Observation: The result is 36'}, {'role': 'assistant', 'content': 'Thought: I need to add 36 and 17'}, {'role': 'assistant', 'content': 'Action: Calculate[36+17]'}, {'role': 'assistant', 'content': 'Observation: The result is 53'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 53'}, {'role': 'assistant', 'content': 'Action: Finish[53]'}, {'role': 'user', 'content': 'Question: Musician and satirist Allie Goertz wrote a song about the \"The Simpsons\" character Milhouse, who Matt Groening named after who?'}, {'role': 'assistant', 'content': 'Thought: The question simplifies to \"The Simpsons\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.'}, {'role': 'assistant', 'content': 'Action: BSearch[Milhouse]'}, {'role': 'assistant', 'content': 'Observation: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell who Milhouse is named after, maybe I can search \"who is Milhouse from The Simpsons named after\".'}, {'role': 'assistant', 'content': 'Action: BSearch[who is Milhouse from The Simpsons named after]'}, {'role': 'assistant', 'content': 'Observation: Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.'}, {'role': 'assistant', 'content': 'Thought: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.'}, {'role': 'assistant', 'content': 'Action: Finish[Richard Nixon]'}, {'role': 'user', 'content': 'Question: Which magazine was started first Arthur’s Magazine or First for Women?'}, {'role': 'assistant', 'content': 'Thought: I need to search Arthur’s Magazine and First for Women, and find which was started first.'}, {'role': 'assistant', 'content': 'Action: BSearch[Arthur’s Magazine]'}, {'role': 'assistant', 'content': 'Observation: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.'}, {'role': 'assistant', 'content': 'Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.'}, {'role': 'assistant', 'content': 'Action: BSearch[First for Women]'}, {'role': 'assistant', 'content': 'Observation: First for Women offers free things, advice, cooking tips, and other articles.'}, {'role': 'assistant', 'content': 'Thought: The paragraph does not tell when the publication started, I should try revising my search to get more relevant responses.'}, {'role': 'assistant', 'content': 'Action: BSearch[when was First for Women first published?]'}, {'role': 'assistant', 'content': 'Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.'}, {'role': 'assistant', 'content': 'Thought: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.'}, {'role': 'assistant', 'content': 'Action: Finish[Arthur’s Magazine]'}, {'role': 'user', 'content': 'Question: How many major charecters are in One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka, combined?'}, {'role': 'assistant', 'content': 'Thought: I need to search for the number of major charecters in One Piece, Game of Thrones, and The Metamotphosis, then I need to add those numbers.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece has 1,100+ charecters.'}, {'role': 'assistant', 'content': 'Thought: This seems like too many charecters to be major charecters. I should try looking for a similar word to \"major\", like \"protagonist\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many protagonists are in One Piece?]'}, {'role': 'assistant', 'content': 'Observation: One Piece is based on a band of 10 pirates'}, {'role': 'assistant', 'content': 'Thought: One Piece has 10 major charecters. I need to search for Game of Thrones next.\".'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in Game of Thrones?]'}, {'role': 'assistant', 'content': 'Observation: Game of Thrones has 52 main charecters'}, {'role': 'assistant', 'content': 'Thought: Game of Thrones has 52 major charecters. I need to search for The Metamorphosis by Franz Kafka next.'}, {'role': 'assistant', 'content': 'Action: BSearch[How many major charecters are in The Metamorphosis by Franz Kafka?]'}, {'role': 'assistant', 'content': 'Observation: The charecter list lists \"Gregor Samsa\", \"Grete Samsa\", \"The Father\", \"The Mother\", \"The Charwoman\", \"The Office Manager\", \"Three temporary boarders\", and \"The Maid\"'}, {'role': 'assistant', 'content': 'Thought: The Metamorphosis by Franz Kafka has 10 major charecters. I now need to add the charecters from One Piece, Game of Thrones, and The Metamorphosis by Franz Kafka.'}, {'role': 'assistant', 'content': 'Action: Calculate[10+52+10]'}, {'role': 'assistant', 'content': 'Observation: The result is 72'}, {'role': 'assistant', 'content': 'Thought: The calculation is done, so the answer is 72'}, {'role': 'assistant', 'content': 'Action: Finish[72]'}, {'role': 'user', 'content': 'Question:What is the distance between the most northern town in the world, and the most southern town in the world?'}, {'role': 'assistant', 'content': 'Thought: The most northern town in the world is Longyearbyen, Svalbard, Norway; the most southern town is Puerto Toro, Chile. I need to search for the distance between Longyearbyen and Puerto Toro.'}, {'role': 'assistant', 'content': 'Action: BSearch[distance between Longyearbyen and Puerto Toro]'}, {'role': 'assistant', 'content': 'Observation: The distance between Longyearbyen, Svalbard, Norway, and Puerto Toro, Chile is not directly provided in the search result. However, with Longyearbyen being situated at 78°13′ N and 818 miles from the North Pole, and Puerto Toro located at 55°05′00″S on the eastern coast of Navarino Island, one would need to utilize a distance calculator tool or perform a more targeted search to determine the direct or travel distance between these two locations.'}, {'role': 'assistant', 'content': \"Thought: I need to search for a more direct answer or use a geographic distance calculator to determine the distance between Longyearbyen and Puerto Toro. Since I don't have access to such a tool, I can only perform a search. I will adjust the search terms to hopefully yield a result that directly states the distance.\"}, {'role': 'assistant', 'content': 'Action: BSearch[distance from Longyearbyen, Norway to Puerto Toro, Chile]'}, {'role': 'assistant', 'content': 'Observation: The distance between Longyearbyen, Norway, and Puerto Williams, Chile (close to Puerto Toro), is approximately 15784.4 kilometers (km). Note that this figure may represent a direct air travel distance and actual travel distance could vary depending on the route taken.'}, {'role': 'assistant', 'content': 'Thought: The distance provided is for Longyearbyen to Puerto Williams, which is near Puerto Toro. The actual distance would be very slightly more than this, but for most intents and purposes, this distance would suffice as a good estimate for the distance between the most northern and the most southern towns in the world. The answer is approximately 15,784.4 kilometers.'}]\n",
            "==========\n",
            "{'role': 'assistant', 'content': 'Action: Finish[Approximately 15,784.4 kilometers]'}\n",
            "model response\n",
            "{'role': 'assistant', 'content': 'Action: Finish[Approximately 15,784.4 kilometers]'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#only printing out the thought process, not the context used to inform the model\n",
        "for i, element in enumerate(a.working_context[68:]):\n",
        "    print('{} - {}'.format(i,element['content']))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AM_WI3YytHLr",
        "outputId": "f3988e10-00fa-4beb-eb08-c1002283d028"
      },
      "execution_count": 223,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 - Question:What is the distance between the most northern town in the world, and the most southern town in the world?\n",
            "1 - Thought: The most northern town in the world is Longyearbyen, Svalbard, Norway; the most southern town is Puerto Toro, Chile. I need to search for the distance between Longyearbyen and Puerto Toro.\n",
            "2 - Action: BSearch[distance between Longyearbyen and Puerto Toro]\n",
            "3 - Observation: The distance between Longyearbyen, Svalbard, Norway, and Puerto Toro, Chile is not directly provided in the search result. However, with Longyearbyen being situated at 78°13′ N and 818 miles from the North Pole, and Puerto Toro located at 55°05′00″S on the eastern coast of Navarino Island, one would need to utilize a distance calculator tool or perform a more targeted search to determine the direct or travel distance between these two locations.\n",
            "4 - Thought: I need to search for a more direct answer or use a geographic distance calculator to determine the distance between Longyearbyen and Puerto Toro. Since I don't have access to such a tool, I can only perform a search. I will adjust the search terms to hopefully yield a result that directly states the distance.\n",
            "5 - Action: BSearch[distance from Longyearbyen, Norway to Puerto Toro, Chile]\n",
            "6 - Observation: The distance between Longyearbyen, Norway, and Puerto Williams, Chile (close to Puerto Toro), is approximately 15784.4 kilometers (km). Note that this figure may represent a direct air travel distance and actual travel distance could vary depending on the route taken.\n",
            "7 - Thought: The distance provided is for Longyearbyen to Puerto Williams, which is near Puerto Toro. The actual distance would be very slightly more than this, but for most intents and purposes, this distance would suffice as a good estimate for the distance between the most northern and the most southern towns in the world. The answer is approximately 15,784.4 kilometers.\n",
            "8 - Action: Finish[Approximately 15,784.4 kilometers]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "QRid4_33toNM"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}